Just like human personal assistants, digital assistants or virtual assistants can perform requested tasks and provide requested advice, information, or services. An assistant's ability to fulfill a user's request is dependent on the assistant's correct comprehension of the request or instructions. Recent advances in natural language processing have enabled users to interact with digital assistants using natural language, in spoken or textual forms, rather than employing a conventional user interface (e.g., menus or programmed commands). Such digital assistants can interpret the user's input to infer the user's intent, translate the inferred intent into actionable tasks and parameters, execute operations or deploy services to perform the tasks, and produce outputs that are intelligible to the user. Ideally, the outputs produced by a digital assistant should fulfill the user's intent expressed during the natural language interaction between the user and the digital assistant.
However, many digital assistants are merely reactive, in that they provide outputs to the user only in response to a user's requests for information. For example, a digital assistant will provide driving directions when a user asks for them, will set an alarm, search the web, or the like. But by only reacting to overt requests for information, the helpfulness of digital assistants is inherently limited. Human personal assistants, on the other hand, are proactive. They can determine what information a person may need and provide it before it is requested. And they can determine whether and how to interrupt a user to provide such information in the most appropriate manner.
Accordingly, there is a need for methods of operating a digital assistant that intelligently and intuitively determine information to provide to a user, without first receiving a specific request for it, and intelligently determine what information warrants interrupting a user, and how to present that information in an appropriate manner.